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Supervised and Unsupervised Learning for Data Science (Paperback, 1st ed. 2020)
Loot Price: R2,789
Discovery Miles 27 890
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Supervised and Unsupervised Learning for Data Science (Paperback, 1st ed. 2020)
Series: Unsupervised and Semi-Supervised Learning
Expected to ship within 10 - 15 working days
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This book covers the state of the art in learning algorithms with
an inclusion of semi-supervised methods to provide a broad scope of
clustering and classification solutions for big data applications.
Case studies and best practices are included along with theoretical
models of learning for a comprehensive reference to the field. The
book is organized into eight chapters that cover the following
topics: discretization, feature extraction and selection,
classification, clustering, topic modeling, graph analysis and
applications. Practitioners and graduate students can use the
volume as an important reference for their current and future
research and faculty will find the volume useful for assignments in
presenting current approaches to unsupervised and semi-supervised
learning in graduate-level seminar courses. The book is based on
selected, expanded papers from the Fourth International Conference
on Soft Computing in Data Science (2018). Includes new advances in
clustering and classification using semi-supervised and
unsupervised learning; Address new challenges arising in feature
extraction and selection using semi-supervised and unsupervised
learning; Features applications from healthcare, engineering, and
text/social media mining that exploit techniques from
semi-supervised and unsupervised learning.
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